Equinix
Website:
equinix.com
Company:
https://www.linkedin.com/company/equinix
Seniority: Not Applicable
Industries: IT Services and IT Consulting
Job details:
Who are we?
Equinix is the world’s digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet.
A place where bold ideas are welcomed, human connection is valued, and everyone has the opportunity to shape their future.
Help us challenge assumptions, uncover bias, and remove barriers—because progress starts with fresh ideas. You’ll find belonging, purpose, and a team that welcomes you—because when you feel valued, you’re empowered to do your best work.
Job Summary
We are seeking a seasoned AI Engineer with 5-7 years of industry experience and proven expertise in designing, developing, and deploying AI agents and generative AI solutions in production environments. The ideal candidate will own the end-to-end lifecycle of LLM-powered applications and AI-driven features, from problem definition, solution architecture, and model integration to deployment, evaluation, monitoring, and continuous optimization.
This role sits at the intersection of software engineering and applied AI, requiring a strong ability to translate business requirements into scalable, production-ready solutions. You will work extensively on integrating large language models and AI agents into enterprise applications and services, while ensuring reliability, performance, security, and measurable business impact. Success in this role demands equal strength in building robust software systems and leveraging cutting-edge AI technologies to solve real-world problems.
Responsibilities
- Design, develop, and deploy production-grade LLM, multimodal AI, and generative AI solutions, owning the entire application lifecycle - integration, monitoring, and continuous optimization
- Implement, and optimize Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, embeddings, vector databases, retrieval strategies, chunking methodologies, and prompt engineering, with clearly defined and measurable quality metrics
- Integrate AI models and agents into enterprise applications, backend services, and APIs, ensuring scalability, reliability, security, cost efficiency, and low-latency performance in production environments
- Collaborate closely with product, engineering, delivery, and business stakeholders to translate business requirements into AI-driven solutions, ensuring technical decisions align with strategic objectives and deliver measurable business outcomes
- Drive continuous improvement of AI systems through experimentation, performance analysis, user feedback, and emerging advancements in generative AI technologies and frameworks
Qualifications
- 5-7 years of software engineering experience, including 2–3 years of hands-on experience designing, deploying, and operating AI/ML solutions in production environments
- Strong proficiency in Python and solid software engineering fundamentals, including data processing, API development and integration, distributed systems, and model serving
- Proficiency in Postgres SQL is required; experience with Java, Node.js, or Scala is a plus
- Familiarity with Model Context Protocol (MCP) and experience building, integrating, or consuming MCP servers, tools, and agent ecosystems
- Demonstrated experience working with Large Language Models (LLMs), multimodal AI, and generative AI technologies, including agentic workflows, Retrieval-Augmented Generation (RAG), prompt engineering, and AI application development
- Hands-on expertise with modern AI/ML frameworks and orchestration tools, such as PyTorch, LangChain, LangGraph, LlamaIndex, or equivalent technologies
- Working experience with cloud-native AI platforms, with a strong preference for AWS services (e.g., Bedrock, SageMaker)
- Proven track record of delivering AI-driven solutions that generate measurable business value, improve operational efficiency, or enhance customer experiences
- Excellent collaboration, stakeholder management, and communication skills, with the ability to work effectively across engineering, product, delivery, and business teams
- Demonstrated ability to work with a high degree of ownership, accountability, and attention to detail while managing complex, multi-component AI systems in dynamic environments
Nice to Have
- Experience with containerization, deployment, and inference serving technologies, including Docker, FastAPI, Kubernetes, vLLM, Ollama, or similar tools
- Ability to visualize, interpret, and communicate AI-generated insights through modern analytics platforms, dashboards, and reporting tools
- Contributions to AI/ML open-source projects, research initiatives, or production-scale AI innovation programs are highly desirable
Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability. If you are a qualified candidate and need assistance or an accommodation, please let us know by completing this form.
Equinix is an Equal Employment Opportunity and, in the U.S., an Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law.
We use artificial intelligence in our hiring process. Learn more here.
This posting is for a backfill position, meaning it is to fill an existing vacancy within our organization.
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